Ordinal Programmatic Weak Supervision and Crowdsourcing for Estimating Cognitive States (Student Abstract)

Prakruthi Pradeep, Benedikt Boecking, Nicholas Gisolfi, Jacob R. Kintz, Torin K. Clark, Artur Dubrawski

AAAI 2023 pp. 16304-16305

doi:10.1609/AAAI.V37I13.27012 /aaai/2023/pradeep2023aaai-ordinal/

Abstract

Crowdsourcing and weak supervision offer methods to efficiently label large datasets. Our work builds on existing weak supervision models to accommodate ordinal target classes, in an effort to recover ground truth from weak, external labels. We define a parameterized factor function and show that our approach improves over other baselines.

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Cite

Text

Pradeep et al. "Ordinal Programmatic Weak Supervision and Crowdsourcing for Estimating Cognitive States (Student Abstract)." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I13.27012

Markdown

[Pradeep et al. "Ordinal Programmatic Weak Supervision and Crowdsourcing for Estimating Cognitive States (Student Abstract)." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/pradeep2023aaai-ordinal/) doi:10.1609/AAAI.V37I13.27012

BibTeX

@inproceedings{pradeep2023aaai-ordinal,
  title     = {{Ordinal Programmatic Weak Supervision and Crowdsourcing for Estimating Cognitive States (Student Abstract)}},
  author    = {Pradeep, Prakruthi and Boecking, Benedikt and Gisolfi, Nicholas and Kintz, Jacob R. and Clark, Torin K. and Dubrawski, Artur},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2023},
  pages     = {16304-16305},
  doi       = {10.1609/AAAI.V37I13.27012},
  url       = {https://mlanthology.org/aaai/2023/pradeep2023aaai-ordinal/}
}